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Record W6901666052 · doi:10.60692/r9834-89d47

Hypertensive disorders of pregnancy and long‐term cardiovascular health: FIGO Best Practice Advice

2023· article· en· W6901666052 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFigshare · 2023
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsWomen's College HospitalUniversity of TorontoKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsPregnancyDiseasePsychological interventionPreeclampsiaRisk factorPostpartum periodDeveloped country

Abstract

fetched live from OpenAlex

Abstract Hypertensive disorders of pregnancy (HDP) are the most common causes of maternal and perinatal morbidity and mortality. They are responsible for 16% of maternal deaths in high‐income countries and approximately 25% in low‐ and middle‐income countries. The impact of HDP can be lifelong as they are a recognized risk factor for future cardiovascular disease. During pregnancy, the cardiovascular system undergoes significant adaptive changes that ensure adequate uteroplacental blood flow and exchange of oxygen and nutrients to nurture and accommodate the developing fetus. Failure to achieve normal cardiovascular adaptation is associated with the development of HDP. Hemodynamic alterations in women with a history of HDP can persist for years and predispose to long‐term cardiovascular morbidity and mortality. Therefore, pregnancy and the postpartum period are an opportunity to identify women with underlying, often unrecognized, cardiovascular risk factors. It is important to develop strategies with lifestyle and therapeutic interventions to reduce the risk of future cardiovascular disease in those who have a history of HDP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.846
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.305
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it